Distances and Similarities in Intuitionistic Fuzzy Sets

This book presents the state-of-the-art in theory and practice regarding similarity and distance measures for intuitionistic fuzzy sets. Quantifying similarity and distances is crucial for many applications, e.g. data mining, machine learning, decision making, and control. The work provides readers...

Full description

Bibliographic Details
Published in:Springer eBooks
Main Author: Szmidt, Eulalia (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
Series:Studies in Fuzziness and Soft Computing,
Subjects:
Online Access:http://dx.doi.org/10.1007/978-3-319-01640-5
Перейти в каталог НБ ТГУ
LEADER 02775nam a22004815i 4500
001 vtls000542103
003 RU-ToGU
005 20210922082208.0
007 cr nn 008mamaa
008 160915s2014 gw | s |||| 0|eng d
020 |a 9783319016405  |9 978-3-319-01640-5 
024 7 |a 10.1007/978-3-319-01640-5  |2 doi 
035 |a to000542103 
039 9 |y 201609152148  |z Александр Эльверович Гилязов 
040 |a Springer  |c Springer  |d RU-ToGU 
050 4 |a Q342 
072 7 |a UYQ  |2 bicssc 
072 7 |a COM004000  |2 bisacsh 
082 0 4 |a 006.3  |2 23 
100 1 |a Szmidt, Eulalia.  |e author.  |9 447449 
245 1 0 |a Distances and Similarities in Intuitionistic Fuzzy Sets  |h electronic resource  |c by Eulalia Szmidt. 
260 |a Cham :  |b Springer International Publishing :  |b Imprint: Springer,  |c 2014.  |9 742221 
300 |a VIII, 148 p. 35 illus., 17 illus. in color.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Studies in Fuzziness and Soft Computing,  |x 1434-9922 ;  |v 307 
505 0 |a Intuitionistic Fuzzy Sets as a Generalization of Fuzzy Sets -- Distances -- Similarity Measures between Intuitionistic Fuzzy Sets. 
520 |a This book presents the state-of-the-art in theory and practice regarding similarity and distance measures for intuitionistic fuzzy sets. Quantifying similarity and distances is crucial for many applications, e.g. data mining, machine learning, decision making, and control. The work provides readers with a comprehensive set of theoretical concepts and practical tools for both defining and determining similarity between intuitionistic fuzzy sets. It describes an automatic algorithm for deriving intuitionistic fuzzy sets from data, which can aid in the analysis of information in large databases. The book also discusses other important applications, e.g. the use of similarity measures to evaluate the extent of agreement between experts in the context of decision making. 
650 0 |a engineering.  |9 224332 
650 0 |a Artificial intelligence.  |9 274099 
650 1 4 |a Engineering.  |9 224332 
650 2 4 |a Computational Intelligence.  |9 307538 
650 2 4 |a Operations Research, Management Science.  |9 353130 
650 2 4 |a Artificial Intelligence (incl. Robotics).  |9 274102 
710 2 |a SpringerLink (Online service)  |9 143950 
773 0 |t Springer eBooks 
830 0 |a Studies in Fuzziness and Soft Computing,  |9 566478 
856 4 0 |u http://dx.doi.org/10.1007/978-3-319-01640-5 
856 |y Перейти в каталог НБ ТГУ  |u https://koha.lib.tsu.ru/cgi-bin/koha/opac-detail.pl?biblionumber=399605 
912 |a ZDB-2-ENG 
950 |a Engineering (Springer-11647) 
999 |c 399605  |d 399605